Date: Wed, 15 Jan 1997 01:04:23 GMT
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<TITLE>Barak Pearlmutter Technical Interests</TITLE>
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<h1>Technical Interests</h1>

    My primary technical interest is in systems that adapt: how to
    analyze them, how to under stand them, how to build them. Because
    the most flexible and competent adaptive systems available to us
    are nervous systems, I'm interested in artificial neural networks
    and computational neuroscience. I'm most fascinated by the
    construction of novel architectures and algorithms that enable us
    to understand and attack previously unassailable problems, and to
    understand previously mysterious aspects of nervous system
    function.
<p>
    To be specific, right now I have a few research topics simmering
    on the front burner:
<ul>

 <li><em>Blind source separation:</em> I'm working on better and more
    modular and incremental methods to solve the cocktail party
    problem, both in the classic (linear square mixing matrix) and in
    the more difficult (fewer microphones than sources) cases.

 <p> <li><em>Reinforcement learning in a weakly adversarial
    domain:</em> In the real world, one's actions modify the world,
    typically to the detriment of similar actions in the future.  I'd
    like to understand how to perform as well as possible, under the
    circumstances.

 <p> <li><em>Neural information and coding:</em> How is information
    represented and transformed in the nervous system?  How are
    these representations acquired and adapted?

 <p> <li><em>Egomotion:</em> The process of estimating a camera's
    motion efficiently, reliably, robustly, and using beautiful
    mathematics.

 <p> <li><em>Neural networks:</em> Learning algorithms,
    generalization, relations to other techniques, handling time and
    domain drift in a principled fashion, unsupervised learning,
    information theory.
</ul>
<p>
    A secondary interest of mine is in programming systems, especially
    advanced programming language design and implementation. There are
    a number of deficiencies in current advanced programming languages
    that hinder their application to scientific computation, and I
    would enjoy participating in an effort to remove these stumbling
    blocks.

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<ADDRESS>
<!WA0><a href=http://www.cs.unm.edu/~bap/index.html>Barak Pearlmutter</a>	<BR>
<!WA1><A HREF="mailto:bap@cs.unm.edu">bap@cs.unm.edu</A>
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